diff --git a/NAMESPACE b/NAMESPACE
index 3d729d7..336d980 100644
--- a/NAMESPACE
+++ b/NAMESPACE
@@ -67,6 +67,7 @@ importFrom(pheatmap,pheatmap)
 importFrom(stats,as.formula)
 importFrom(stats,median)
 importFrom(stats,sd)
+importFrom(stats,setNames)
 importFrom(utils,modifyList)
 importFrom(utils,packageVersion)
 importFrom(utils,read.table)
diff --git a/R/ColorAdjustments.R b/R/ColorAdjustments.R
index db7e7c0..360fc79 100644
--- a/R/ColorAdjustments.R
+++ b/R/ColorAdjustments.R
@@ -2,7 +2,7 @@
 #' Darkens input colors by a set amount
 #'
 #' @description A wrapper for the darken function of the colorspace package.
-#' @param colors the color(s) input. Can be a list of colors, for example, /code{dittoColors()}.
+#' @param colors the color(s) input. Can be a list of colors, for example, \code{dittoColors()}.
 #' @param percent.change # between 0 and 1. the percentage to darken by. Defaults to 0.25 if not given.
 #' @param relative TRUE/FALSE. Whether the percentage should be a relative change versus an absolute one. Default = TRUE.
 #' @return Return a darkened version of the color in hexadecimal color form (="#RRGGBB" in base 16)
@@ -23,7 +23,7 @@ Darken <- function(colors, percent.change = 0.25, relative = TRUE) {
 #' Lightens input colors by a set amount
 #'
 #' @description A wrapper for the lighten function of the colorspace package.
-#' @param colors the color(s) input. Can be a list of colors, for example, /code{dittoColors()}.
+#' @param colors the color(s) input. Can be a list of colors, for example, \code{dittoColors()}.
 #' @param percent.change # between 0 and 1. the percentage to darken by. Defaults to 0.25 if not given.
 #' @param relative TRUE/FALSE. Whether the percentage should be a relative change versus an absolute one. Default = TRUE.
 #' @return Return a lighter version of the color in hexadecimal color form (="#RRGGBB" in base 16)
diff --git a/R/DittoDimPlot.R b/R/DittoDimPlot.R
index 6fedbf3..d53d07c 100644
--- a/R/DittoDimPlot.R
+++ b/R/DittoDimPlot.R
@@ -70,7 +70,7 @@
 #' @param shape.legend.title String which sets the title of the shapes legend.  Default is \code{shape.by}
 #' @param assay,slot single strings or integers (SCEs and SEs) or an optionally named vector of such values that set which expression data to use.
 #' See \code{\link{GeneTargeting}} for specifics and examples -- Seurat and SingleCellExperiment objects deal with these differently, and functionality additions in dittoSeq have led to some minimal divergence from the native methodologies.
-#' @param adjustment When plotting gene / feature expression, should that data be used directly (default) or should it be adjusted to be
+#' @param adjustment \code{NULL} for off or a recognized string indicating if numeric \code{var}-data should be used directly (default) or should be adjusted to be
 #' \itemize{
 #' \item{"z-score": scaled with the scale() function to produce a relative-to-mean z-score representation}
 #' \item{"relative.to.max": divided by the maximum expression value to give percent of max values between [0,1]}
diff --git a/R/DittoScatterPlot.R b/R/DittoScatterPlot.R
index 271e8e0..9ec2b35 100644
--- a/R/DittoScatterPlot.R
+++ b/R/DittoScatterPlot.R
@@ -33,7 +33,7 @@
 #' @param colors Integer vector, the indexes / order, of colors from color.panel to actually use
 #' @param assay.x,assay.y,assay.color,assay.extra,slot.x,slot.y,slot.color,slot.extra single strings or integers (SCEs and SEs) or an optionally named vector of such values that set which expression data to use for each given data target.
 #' See \code{\link{GeneTargeting}} for specifics and examples -- Seurat and SingleCellExperiment objects deal with these differently, and functionality additions in dittoSeq have led to some minimal divergence from the native methodologies.
-#' @param adjustment.x,adjustment.y,adjustment.color,adjustment.extra For the given data target, when targeting gene / feature expression, should that data be used directly (default) or should it be adjusted to be
+#' @param adjustment.x,adjustment.y,adjustment.color,adjustment.extra \code{NULL} for off or a recognized string indicating if, for the given data target, when targeting numeric data, that data should be used directly (default) or should be adjusted to be
 #' \itemize{
 #' \item{"z-score": scaled with the scale() function to produce a relative-to-mean z-score representation}
 #' \item{"relative.to.max": divided by the maximum expression value to give percent of max values between [0,1]}
diff --git a/R/dittoDotPlot.R b/R/dittoDotPlot.R
index d80436c..e50a484 100644
--- a/R/dittoDotPlot.R
+++ b/R/dittoDotPlot.R
@@ -22,9 +22,9 @@
 #' adding \code{theme(strip.placement = "outside", strip.background.y = element_blank())} to the given \code{theme} (or 'x' counterpart depending on \code{vars.dir})
 #' @param summary.fxn.color,summary.fxn.size A function which sets how color or size will be used to summarize variables' data for each group.
 #' Any function can be used as long as it takes in a numeric vector and returns a single numeric value.
-#' @param scale String which sets whether the values shown with color (default: mean non-zero expression) should be centered and scaled. 
+#' @param scale String which sets whether the values shown with color should be centered and scaled after being summarized per \code{group.by} groups. 
 #' @param size Number which sets the visual dot size associated with the highest value shown by dot size (default: percent non-zero expression).
-#' @param adjustment Should expression data be used directly (default) or should it be adjusted to be
+#' @param adjustment \code{NULL} for off or a recognized string indicating if \code{vars}-data should be used directly (default) or, prior to any potential scaling per groupings controlled via \code{scale}, should be adjusted to be
 #' \itemize{
 #' \item{"z-score": scaled with the scale() function to produce a relative-to-mean z-score representation}
 #' \item{"relative.to.max": divided by the maximum expression value to give percent of max values between [0,1]}
@@ -597,7 +597,7 @@ dittoDotPlot <- function(
     )
 }
 
-#' @importFrom stats sd
+#' @importFrom stats sd setNames
 .multi_var_gather_raw <- function(
     object,
     vars,
@@ -623,7 +623,18 @@ dittoDotPlot <- function(
     }
     
     gets_data <- if (length(meta_gets)>0) {
-        getMetas(object, names.only = FALSE)[, meta_gets, drop = FALSE]
+        data.frame(
+            setNames(
+                lapply(
+                    meta_gets,
+                    function(m) {
+                        # Individual pulls for applying adjustments
+                        meta(m, object, adjustment, add.names = FALSE)
+                    }
+                ),
+                meta_gets),
+            row.names = .all_cells(object)
+        )
     } else {
         data.frame(row.names = .all_cells(object))
     }
diff --git a/R/dittoPlot.R b/R/dittoPlot.R
index a078c8a..b391030 100644
--- a/R/dittoPlot.R
+++ b/R/dittoPlot.R
@@ -37,7 +37,7 @@
 #' See details section for more info.
 #' @param assay,slot single strings or integers (SCEs and SEs) or an optionally named vector of such values that set which expression data to use.
 #' See \code{\link{GeneTargeting}} for specifics and examples -- Seurat and SingleCellExperiment objects deal with these differently, and functionality additions in dittoSeq have led to some minimal divergence from the native methodologies.
-#' @param adjustment When plotting gene expression / feature counts, should that data be used directly (default) or should it be adjusted to be
+#' @param adjustment \code{NULL} for off or a recognized string indicating if \code{var}-data should be used directly (default) or should be adjusted to be
 #' \itemize{
 #' \item{"z-score": scaled with the scale() function to produce a relative-to-mean z-score representation}
 #' \item{"relative.to.max": divided by the maximum expression value to give percent of max values between [0,1]}
diff --git a/R/dittoPlotVarsAcrossGroups.R b/R/dittoPlotVarsAcrossGroups.R
index 08a80e8..43c0138 100644
--- a/R/dittoPlotVarsAcrossGroups.R
+++ b/R/dittoPlotVarsAcrossGroups.R
@@ -15,7 +15,7 @@
 #' @param plots String vector which sets the types of plots to include: possibilities = "jitter", "boxplot", "vlnplot", "ridgeplot".
 #' Order matters: c("vlnplot", "boxplot", "jitter") will put a violin plot in the back, boxplot in the middle, and then individual dots in the front.
 #' See details section for more info.
-#' @param adjustment When plotting gene expression (or antibody, or other forms of counts data), should that data be used directly or should it be adjusted to be
+#' @param adjustment \code{NULL} for off or a recognized string indicating if \code{var}-data should be used directly or should be adjusted to be
 #' \itemize{
 #' \item{"z-score": DEFAULT, centered and scaled to produce a relative-to-mean z-score representation}
 #' \item{NULL: no adjustment, the normal method for all other ditto expression plotting functions}
diff --git a/R/gene-getters.R b/R/gene-getters.R
index 902f750..de55702 100644
--- a/R/gene-getters.R
+++ b/R/gene-getters.R
@@ -110,7 +110,7 @@ getGenes <- function(
 #' @param object A Seurat, SingleCellExperiment, or SummarizedExperiment object.
 #' @param assay,slot single strings or integers (SCEs and SEs) or a vector of such values that set which expression data to use.
 #' See \code{\link{GeneTargeting}} for specifics and examples -- Seurat and SingleCellExperiment objects deal with these differently, and functionality additions in dittoSeq have led to some minimal divergence from the native methodologies.
-#' @param adjustment Should expression data be used directly (default) or should it be adjusted to be
+#' @param adjustment \code{NULL} for off or a recognized string indicating if expression data should be used directly (default) or should instead be adjusted to be
 #' \itemize{
 #' \item{"z-score": scaled with the scale() function to produce a relative-to-mean z-score representation}
 #' \item{"relative.to.max": divided by the maximum expression value to give percent of max values between [0,1]}
diff --git a/R/meta-getters.R b/R/meta-getters.R
index d36d0c8..a358852 100644
--- a/R/meta-getters.R
+++ b/R/meta-getters.R
@@ -86,11 +86,11 @@ getMetas <- function(object, names.only = TRUE){
 }
 
 #### meta: for extracting the values of a particular metadata for all cells/samples ####
-#' Returns the values of a meta.data  for all cells/samples
+#' Returns the values of a meta.data for all cells/samples
 #'
 #' @param meta String, the name of the "metadata" slot to grab. OR "ident" to retireve the clustering of a Seurat \code{object}.
 #' @param object A Seurat, SingleCellExperiment, or SummarizedExperiment object.
-#' @param adjustment A recognized string indicating whether numeric metadata should be used directly (default) versus adjusted to be
+#' @param adjustment \code{NULL} for off or a recognized string indicating whether numeric metadata should be used directly (default) versus adjusted to be
 #' \itemize{
 #' \item{"z-score": scaled with the scale() function to produce a relative-to-mean z-score representation}
 #' \item{"relative.to.max": divided by the maximum expression value to give percent of max values between [0,1]}
@@ -100,14 +100,15 @@ getMetas <- function(object, names.only = TRUE){
 #' @param adj.fxn A function which takes a vector (of metadata values) and returns a vector of the same length.
 #' 
 #' For example, \code{function(x) \{log2(x)\}} or \code{as.factor}
-#' @return A named vector.
+#' @param add.names Logical which sets whether cells'/samples' names should be added as names on the output.
+#' @return A vector
 #' @details
 #' Retrieves the values of a metadata slot from \code{object}, or the clustering slot if \code{meta = "ident"} and the \code{object} is a Seurat.
 #' 
 #' If \code{adjustment} or \code{adj.fxn} are provided, then these requested adjustments are applied to these values (\code{adjustment} first).
 #' Note: Alterations via \code{adjustment} are only applied when metadata is numeric, but \code{adj.fxn} alterations are applied to metadata of any type.
 #' 
-#' Lastly, outputs these values are named as the cells'/samples' names.
+#' Lastly, if \code{add.names = TRUE} the values are named as the cells'/samples' names before being output. 
 #' @seealso
 #' \code{\link{metaLevels}} for returning just the unique discrete identities that exist within a metadata slot
 #'
@@ -127,7 +128,7 @@ getMetas <- function(object, names.only = TRUE){
 #' @export
 
 meta <- function(meta, object,
-    adjustment = NULL, adj.fxn = NULL) {
+    adjustment = NULL, adj.fxn = NULL, add.names = TRUE) {
 
     if (!isMeta(meta, object)) {
         stop(dQuote(meta)," is not a metadata of 'object'")
@@ -165,7 +166,9 @@ meta <- function(meta, object,
     }
     
     # Add names
-    names(values) <- .all_cells(object)
+    if (add.names) {
+        names(values) <- .all_cells(object)
+    }
     
     values
 }
diff --git a/R/utils-getters.R b/R/utils-getters.R
index 3081480..cd92a02 100644
--- a/R/utils-getters.R
+++ b/R/utils-getters.R
@@ -113,7 +113,7 @@
     
     if (length(var)==1 && is.character(var)) {
         if (isMeta(var, object)) {
-            OUT <- meta(var, object)
+            OUT <- meta(var, object, adjustment)
         } else if (isGene(var, object, assay)) {
             OUT <- gene(var, object, assay, slot, adjustment)
         }
diff --git a/man/Darken.Rd b/man/Darken.Rd
index 6d3156b..71e5307 100644
--- a/man/Darken.Rd
+++ b/man/Darken.Rd
@@ -7,7 +7,7 @@
 Darken(colors, percent.change = 0.25, relative = TRUE)
 }
 \arguments{
-\item{colors}{the color(s) input. Can be a list of colors, for example, /code{dittoColors()}.}
+\item{colors}{the color(s) input. Can be a list of colors, for example, \code{dittoColors()}.}
 
 \item{percent.change}{# between 0 and 1. the percentage to darken by. Defaults to 0.25 if not given.}
 
diff --git a/man/Lighten.Rd b/man/Lighten.Rd
index 82fda89..0fa29be 100644
--- a/man/Lighten.Rd
+++ b/man/Lighten.Rd
@@ -7,7 +7,7 @@
 Lighten(colors, percent.change = 0.25, relative = TRUE)
 }
 \arguments{
-\item{colors}{the color(s) input. Can be a list of colors, for example, /code{dittoColors()}.}
+\item{colors}{the color(s) input. Can be a list of colors, for example, \code{dittoColors()}.}
 
 \item{percent.change}{# between 0 and 1. the percentage to darken by. Defaults to 0.25 if not given.}
 
diff --git a/man/dittoDimPlot.Rd b/man/dittoDimPlot.Rd
index eb0e89d..354863d 100644
--- a/man/dittoDimPlot.Rd
+++ b/man/dittoDimPlot.Rd
@@ -143,7 +143,7 @@ Useful for making custom splitting/faceting or other additional alterations \emp
 \item{assay, slot}{single strings or integers (SCEs and SEs) or an optionally named vector of such values that set which expression data to use.
 See \code{\link{GeneTargeting}} for specifics and examples -- Seurat and SingleCellExperiment objects deal with these differently, and functionality additions in dittoSeq have led to some minimal divergence from the native methodologies.}
 
-\item{adjustment}{When plotting gene / feature expression, should that data be used directly (default) or should it be adjusted to be
+\item{adjustment}{\code{NULL} for off or a recognized string indicating if numeric \code{var}-data should be used directly (default) or should be adjusted to be
 \itemize{
 \item{"z-score": scaled with the scale() function to produce a relative-to-mean z-score representation}
 \item{"relative.to.max": divided by the maximum expression value to give percent of max values between [0,1]}
diff --git a/man/dittoDotPlot.Rd b/man/dittoDotPlot.Rd
index 8512fa9..1fc5bc8 100644
--- a/man/dittoDotPlot.Rd
+++ b/man/dittoDotPlot.Rd
@@ -65,7 +65,7 @@ Example: \code{vars = list('Epithelial Cells' = c("gene1","gene2"), Neuron = c("
 
 \item{group.by}{String representing the name of a metadata to use for separating the cells/samples into discrete groups.}
 
-\item{scale}{String which sets whether the values shown with color (default: mean non-zero expression) should be centered and scaled.}
+\item{scale}{String which sets whether the values shown with color should be centered and scaled after being summarized per \code{group.by} groups.}
 
 \item{split.by}{1 or 2 strings naming discrete metadata to use for splitting the cells/samples into multiple plots with ggplot faceting.
 \itemize{
@@ -135,7 +135,7 @@ When set to NA, the minimum/maximum of the data are used.}
 \item{assay, slot}{single strings or integers (SCEs and SEs) or an optionally named vector of such values that set which expression data to use.
 See \code{\link{GeneTargeting}} for specifics and examples -- Seurat and SingleCellExperiment objects deal with these differently, and functionality additions in dittoSeq have led to some minimal divergence from the native methodologies.}
 
-\item{adjustment}{Should expression data be used directly (default) or should it be adjusted to be
+\item{adjustment}{\code{NULL} for off or a recognized string indicating if \code{vars}-data should be used directly (default) or, prior to any potential scaling per groupings controlled via \code{scale}, should be adjusted to be
 \itemize{
 \item{"z-score": scaled with the scale() function to produce a relative-to-mean z-score representation}
 \item{"relative.to.max": divided by the maximum expression value to give percent of max values between [0,1]}
diff --git a/man/dittoHex.Rd b/man/dittoHex.Rd
index a694de4..85864d7 100644
--- a/man/dittoHex.Rd
+++ b/man/dittoHex.Rd
@@ -201,7 +201,7 @@ OR when giving 2 metadatas to \code{split.by}, see \code{\link[ggplot2]{facet_gr
 \item{assay, slot}{single strings or integers (SCEs and SEs) or an optionally named vector of such values that set which expression data to use.
 See \code{\link{GeneTargeting}} for specifics and examples -- Seurat and SingleCellExperiment objects deal with these differently, and functionality additions in dittoSeq have led to some minimal divergence from the native methodologies.}
 
-\item{adjustment}{When plotting gene / feature expression, should that data be used directly (default) or should it be adjusted to be
+\item{adjustment}{\code{NULL} for off or a recognized string indicating if numeric \code{var}-data should be used directly (default) or should be adjusted to be
 \itemize{
 \item{"z-score": scaled with the scale() function to produce a relative-to-mean z-score representation}
 \item{"relative.to.max": divided by the maximum expression value to give percent of max values between [0,1]}
@@ -298,7 +298,7 @@ Alternatively, can be a directly supplied numeric vector of length equal to the
 \item{assay.x, assay.y, assay.color, assay.extra, slot.x, slot.y, slot.color, slot.extra}{single strings or integers (SCEs and SEs) or an optionally named vector of such values that set which expression data to use for each given data target.
 See \code{\link{GeneTargeting}} for specifics and examples -- Seurat and SingleCellExperiment objects deal with these differently, and functionality additions in dittoSeq have led to some minimal divergence from the native methodologies.}
 
-\item{adjustment.x, adjustment.y, adjustment.color, adjustment.extra}{For the given data target, when targeting gene / feature expression, should that data be used directly (default) or should it be adjusted to be
+\item{adjustment.x, adjustment.y, adjustment.color, adjustment.extra}{\code{NULL} for off or a recognized string indicating if, for the given data target, when targeting numeric data, that data should be used directly (default) or should be adjusted to be
 \itemize{
 \item{"z-score": scaled with the scale() function to produce a relative-to-mean z-score representation}
 \item{"relative.to.max": divided by the maximum expression value to give percent of max values between [0,1]}
diff --git a/man/dittoPlot.Rd b/man/dittoPlot.Rd
index 83693d2..7492b21 100644
--- a/man/dittoPlot.Rd
+++ b/man/dittoPlot.Rd
@@ -123,7 +123,7 @@ When set to "split", inputs \code{split.nrow}, \code{split.ncol}, and \code{spli
 \item{assay, slot}{single strings or integers (SCEs and SEs) or an optionally named vector of such values that set which expression data to use.
 See \code{\link{GeneTargeting}} for specifics and examples -- Seurat and SingleCellExperiment objects deal with these differently, and functionality additions in dittoSeq have led to some minimal divergence from the native methodologies.}
 
-\item{adjustment}{When plotting gene expression / feature counts, should that data be used directly (default) or should it be adjusted to be
+\item{adjustment}{\code{NULL} for off or a recognized string indicating if \code{var}-data should be used directly (default) or should be adjusted to be
 \itemize{
 \item{"z-score": scaled with the scale() function to produce a relative-to-mean z-score representation}
 \item{"relative.to.max": divided by the maximum expression value to give percent of max values between [0,1]}
diff --git a/man/dittoPlotVarsAcrossGroups.Rd b/man/dittoPlotVarsAcrossGroups.Rd
index 7a3bff2..266836a 100644
--- a/man/dittoPlotVarsAcrossGroups.Rd
+++ b/man/dittoPlotVarsAcrossGroups.Rd
@@ -98,7 +98,7 @@ See details section for more info.}
 \item{assay, slot}{single strings or integers (SCEs and SEs) or an optionally named vector of such values that set which expression data to use.
 See \code{\link{GeneTargeting}} for specifics and examples -- Seurat and SingleCellExperiment objects deal with these differently, and functionality additions in dittoSeq have led to some minimal divergence from the native methodologies.}
 
-\item{adjustment}{When plotting gene expression (or antibody, or other forms of counts data), should that data be used directly or should it be adjusted to be
+\item{adjustment}{\code{NULL} for off or a recognized string indicating if \code{var}-data should be used directly or should be adjusted to be
 \itemize{
 \item{"z-score": DEFAULT, centered and scaled to produce a relative-to-mean z-score representation}
 \item{NULL: no adjustment, the normal method for all other ditto expression plotting functions}
diff --git a/man/dittoScatterPlot.Rd b/man/dittoScatterPlot.Rd
index 17d491f..969d510 100644
--- a/man/dittoScatterPlot.Rd
+++ b/man/dittoScatterPlot.Rd
@@ -139,7 +139,7 @@ OR when giving 2 metadatas to \code{split.by}, see \code{\link[ggplot2]{facet_gr
 \item{assay.x, assay.y, assay.color, assay.extra, slot.x, slot.y, slot.color, slot.extra}{single strings or integers (SCEs and SEs) or an optionally named vector of such values that set which expression data to use for each given data target.
 See \code{\link{GeneTargeting}} for specifics and examples -- Seurat and SingleCellExperiment objects deal with these differently, and functionality additions in dittoSeq have led to some minimal divergence from the native methodologies.}
 
-\item{adjustment.x, adjustment.y, adjustment.color, adjustment.extra}{For the given data target, when targeting gene / feature expression, should that data be used directly (default) or should it be adjusted to be
+\item{adjustment.x, adjustment.y, adjustment.color, adjustment.extra}{\code{NULL} for off or a recognized string indicating if, for the given data target, when targeting numeric data, that data should be used directly (default) or should be adjusted to be
 \itemize{
 \item{"z-score": scaled with the scale() function to produce a relative-to-mean z-score representation}
 \item{"relative.to.max": divided by the maximum expression value to give percent of max values between [0,1]}
diff --git a/man/gene.Rd b/man/gene.Rd
index d987d76..dbbc0d5 100644
--- a/man/gene.Rd
+++ b/man/gene.Rd
@@ -22,7 +22,7 @@ gene(
 \item{assay, slot}{single strings or integers (SCEs and SEs) or a vector of such values that set which expression data to use.
 See \code{\link{GeneTargeting}} for specifics and examples -- Seurat and SingleCellExperiment objects deal with these differently, and functionality additions in dittoSeq have led to some minimal divergence from the native methodologies.}
 
-\item{adjustment}{Should expression data be used directly (default) or should it be adjusted to be
+\item{adjustment}{\code{NULL} for off or a recognized string indicating if expression data should be used directly (default) or should instead be adjusted to be
 \itemize{
 \item{"z-score": scaled with the scale() function to produce a relative-to-mean z-score representation}
 \item{"relative.to.max": divided by the maximum expression value to give percent of max values between [0,1]}
diff --git a/man/meta.Rd b/man/meta.Rd
index 15e8bd1..a04471c 100644
--- a/man/meta.Rd
+++ b/man/meta.Rd
@@ -2,16 +2,16 @@
 % Please edit documentation in R/meta-getters.R
 \name{meta}
 \alias{meta}
-\title{Returns the values of a meta.data  for all cells/samples}
+\title{Returns the values of a meta.data for all cells/samples}
 \usage{
-meta(meta, object, adjustment = NULL, adj.fxn = NULL)
+meta(meta, object, adjustment = NULL, adj.fxn = NULL, add.names = TRUE)
 }
 \arguments{
 \item{meta}{String, the name of the "metadata" slot to grab. OR "ident" to retireve the clustering of a Seurat \code{object}.}
 
 \item{object}{A Seurat, SingleCellExperiment, or SummarizedExperiment object.}
 
-\item{adjustment}{A recognized string indicating whether numeric metadata should be used directly (default) versus adjusted to be
+\item{adjustment}{\code{NULL} for off or a recognized string indicating whether numeric metadata should be used directly (default) versus adjusted to be
 \itemize{
 \item{"z-score": scaled with the scale() function to produce a relative-to-mean z-score representation}
 \item{"relative.to.max": divided by the maximum expression value to give percent of max values between [0,1]}
@@ -22,12 +22,14 @@ Ignored if the target metadata is not numeric.}
 \item{adj.fxn}{A function which takes a vector (of metadata values) and returns a vector of the same length.
 
 For example, \code{function(x) \{log2(x)\}} or \code{as.factor}}
+
+\item{add.names}{Logical which sets whether cells'/samples' names should be added as names on the output.}
 }
 \value{
-A named vector.
+A vector
 }
 \description{
-Returns the values of a meta.data  for all cells/samples
+Returns the values of a meta.data for all cells/samples
 }
 \details{
 Retrieves the values of a metadata slot from \code{object}, or the clustering slot if \code{meta = "ident"} and the \code{object} is a Seurat.
@@ -35,7 +37,7 @@ Retrieves the values of a metadata slot from \code{object}, or the clustering sl
 If \code{adjustment} or \code{adj.fxn} are provided, then these requested adjustments are applied to these values (\code{adjustment} first).
 Note: Alterations via \code{adjustment} are only applied when metadata is numeric, but \code{adj.fxn} alterations are applied to metadata of any type.
 
-Lastly, outputs these values are named as the cells'/samples' names.
+Lastly, if \code{add.names = TRUE} the values are named as the cells'/samples' names before being output.
 }
 \examples{
 example(importDittoBulk, echo = FALSE)
diff --git a/tests/testthat/test-getters.R b/tests/testthat/test-getters.R
index 286f9c0..6ffc9ca 100644
--- a/tests/testthat/test-getters.R
+++ b/tests/testthat/test-getters.R
@@ -1,5 +1,5 @@
 # Tests for visualization functions
-# library(dittoSeq); library(testthat); source("setup.R"); source("../../R/utils.R"); source("../../R/utils-getters.R"); source("../../R/get.reductions.R"); source("../../R/utils-defaulting.R"); source("test-getters.R")
+# library(dittoSeq); library(testthat); for (i in list.files("../../R", pattern="^utils", full.names = TRUE)) source(i); source("test-getters.R")
 
 # Make Seurat, if can
 try(seurat <- Seurat::as.Seurat(sce), silent = TRUE)
@@ -28,7 +28,7 @@ test_that("isMeta works for Seurat and SCE", {
     expect_true(isMeta("score", seurat))
 })
 
-test_that("meta works for Seurat and SCE (+ adjustment/adj.fxn)", {
+test_that("meta works for Seurat and SCE (+ adjustment/adj.fxn, add.names)", {
     expect_type(
         meta("score", sce),
         "double")
@@ -45,6 +45,12 @@ test_that("meta works for Seurat and SCE (+ adjustment/adj.fxn)", {
         factor(meta("score", sce)),
         meta("score", sce, adj.fxn = function(x) {factor(x)}))
     
+    expect_true(is.null(names(meta("age", sce, add.names = FALSE))))
+    expect_equal(
+        names(meta("age", sce)),
+        .all_cells(sce)
+    )
+
     skip_if_not(seurat_conversion_worked, message = "Seurat conversion bug")
     expect_equal(
         meta("score", sce),